Various imaging systems and tools have been developed to assist physicians, clinicians, radiologists, etc. in evaluating medical images to diagnose medical conditions. For example, computer-aided detection (CAD) tools have been developed for various clinical applications to provide automated detection of abnormalities in medical images, such as colonic polyps and other abnormal anatomical structures such as lung nodules, lesions, aneurysms, calcification, in breast, heart or artery tissue, etc.
A common medical imaging technique is magnetic resonance imaging (MRI), which uses a powerful magnetic field to image the internal structure and certain functionality of a body. MRI is particularly suited for imaging soft tissue structures and is thus highly useful in the field of oncology for the detection of breast lesions. Variations in breast MRI techniques and descriptions of morphologic findings, however, often give rise to difficulties among radiologists in describing lesions and communicating the results to physicians for diagnosis and treatment.
To overcome difficulties arising from the lack of standardization, the American College of Radiology developed the BI-RADS-MRI lexicon, published as a part of the American College of Radiology's Breast Imaging Reporting and Data System Atlas. For ease of comparison and reference, it is often recommended that radiologists use the BI-RADS lexicon, in addition to kinetic time-intensity information, to describe the morphology of lesions during clinical analysis of breast MRI.
According to the BI-RADS lexicon, a lesion may be classified according to various morphologic categories. For example, a lesion may be categorized according to its shape (round, oval, lobulated or irregular) or margin (smooth, irregular or speculated). Morphology provides useful clues in identifying whether the lesion is malignant or not. A lesion is more likely to be malignant if it has an irregular shape while a round lesion is more likely benign. A lesion with a speculated margin or rim enhancement is more suspicious than a lesion with dark septations or a lesion with homogenous interior brightness.
One problem with prior techniques arises because each category is evaluated independent of the other categories. Such evaluation often gives rise to self-contradictory descriptions. For example, a lesion may be clinically classified as having both a round shape and a speculated margin. Such classification seems contradictory as a round mass is connotative of benignity, while a speculated margin is connotative of malignancy. Similarly, a descriptor indicating that a lesion has both dark septations and rim enhancement sounds self-contradictory. This may cause confusion during the interpretation of MRI findings, resulting in significant degradation in detection and diagnostic performance.
Therefore, there is a need for a technology that mitigates or obviates the foregoing problems.